The multi-vehicle covering tour problem: building routes for urban patrolling
This work addresses route planning for urban community policing to improve perceived safety and emergency response, but it is incremental as it adapts existing models and heuristics.
The paper tackles the urban patrolling route planning problem by adapting the multi-vehicle covering tour model to ensure visibility and balanced routes, achieving suboptimal solutions through heuristics tested on TSPLIB instances and real data.
In this paper we study a particular aspect of the urban community policing: routine patrol route planning. We seek routes that guarantee visibility, as this has a sizable impact on the community perceived safety, allowing quick emergency responses and providing surveillance of selected sites (e.g., hospitals, schools). The planning is restricted to the availability of vehicles and strives to achieve balanced routes. We study an adaptation of the model for the multi-vehicle covering tour problem, in which a set of locations must be visited, whereas another subset must be close enough to the planned routes. It constitutes an NP-complete integer programming problem. Suboptimal solutions are obtained with several heuristics, some adapted from the literature and others developed by us. We solve some adapted instances from TSPLIB and an instance with real data, the former being compared with results from literature, and latter being compared with empirical data.